Mechanochemical tuning of myosin-I by the N-terminal region

Significance

Myosin molecular motors generate forces in the cell and act as mechanosensors, adjusting their power outputs in response to mechanical loads. Little is known about the structural elements involved in myosin mechanosensing. Our results identify the N-terminal region (NTR) of the myosin-I protein as having an important role in tuning mechanochemistry. Appending the NTR from a highly tension-sensitive myosin (Myo1b) onto a less tension-sensitive motor (Myo1c) changes the identity of the primary force-sensitive transition of Myo1c, making it sensitive to forces <2 pN. Moreover, we show that the NTR stabilizes the post–power-stroke conformation. These results identify the NTR as an important structural element in myosin force sensing and suggest a mechanism for generating diversity of function among myosin isoforms.

Abstract

Myosins are molecular motors that generate force to power a wide array of motile cellular functions. Myosins have the inherent ability to change their ATPase kinetics and force-generating properties when they encounter mechanical loads; however, little is known about the structural elements in myosin responsible for force sensing. Recent structural and biophysical studies have shown that myosin-I isoforms, Myosin-Ib (Myo1b) and Myosin-Ic (Myo1c), have similar unloaded kinetics and sequences but substantially different responses to forces that resist their working strokes. Myo1b has the properties of a tension-sensing anchor, slowing its actin-detachment kinetics by two orders of magnitude with just 1 pN of resisting force, whereas Myo1c has the properties of a slow transporter, generating power without slowing under 1-pN loads that would stall Myo1b. To examine the structural elements that lead to differences in force sensing, we used single-molecule and ensemble kinetic techniques to show that the myosin-I N-terminal region (NTR) plays a critical role in tuning myosin-I mechanochemistry. We found that replacing the Myo1c NTR with the Myo1b NTR changes the identity of the primary force-sensitive transition of Myo1c, resulting in sensitivity to forces of <2 pN. Additionally, we found that the NTR plays an important role in stabilizing the post–power-stroke conformation. These results identify the NTR as an important structural element in myosin force sensing and suggest a mechanism for generating diversity of function among myosin isoforms.

Myosin motors use the energy from ATP hydrolysis to power a wide array of cellular processes including muscle contraction, cell migration, membrane trafficking, cell division, and intracellular transport (for review, see ref. 1). To optimally function in such diverse processes, different myosin isoforms have evolved distinct kinetic and mechanical properties to meet their physiological demands (for review, see ref. 2), including differing abilities to adapt their ATPase kinetics and power outputs in response to mechanical loads (3). Although many studies have elucidated structural elements important for force generation in myosin motors, not much is known about the regions important for tuning a myosin’s ability to modulate power output in response to mechanical loads.

An opportunity to study these structural elements has emerged with the structural and mechanochemical characterization of two myosin-I family members with similar sequences, Myosin-Ib (Myo1b) (4–7) and Myosin-Ic (Myo1c) (8–10). These motors have similar unloaded ATPase kinetics, where they are both low duty-ratio motors (i.e., they spend a majority of their biochemical cycles detached from actin) with motility rates that are limited by the rate of ADP release (7, 10–14). Although these motors have similar sequences and unloaded ATPase kinetics, they have very different mechanical outputs under load (for review, see ref. 15). Myo1b is extraordinarily sensitive to small loads, where forces of 1 pN slow its motility rate more than 50-fold. As such, Myo1b has the expected properties of a tension-sensitive anchor (5, 6). In contrast, 1 pN of force does not appreciably slow the rate of Myo1c motility, enabling the motor to generate power over a range of forces. Thus, Myo1c has the expected properties of a slow transporter (10). Not only do these myosins have different responses to force, but also they have different biochemical transitions that are affected by force (i.e., the rate of ADP release for Myo1b and the rate of ATP-induced actomyosin detachment for Myo1c).

The high-resolution crystal structures of nucleotide-free Myo1b (i.e., rigor-like state) (4) and ADP.vanadate-bound Myo1c (i.e., pre–power-stroke state) (8) have recently been determined. Despite being in different conformational states, these structures show that Myo1b and Myo1c have a high degree of structural homology to each other and to other myosins (4, 16). A prominent feature in the Myo1b structure is the positioning of the N-terminal region (NTR), which is in a conformation that has not been observed in other myosin structures (Fig. 1A). In myosin-II, -V, and -VI the NTR includes an SH3-like domain that lies to the side of the motor domain (17–19). In contrast, the Myo1b NTR sits in a hydrophobic pocket between the motor and the lever arm helix (LAH) and interacts with the first calmodulin light chain. As such, it is in a position that might enable it to communicate the position of the LAH to the nucleotide-binding site (4). Although the motor domain sequences of myosin-I isoforms are highly conserved, including the residues that create the hydrophobic pocket in which the NTR sits, the NTR sequences are not conserved (Fig. 1B). We hypothesized that the NTR plays a role in establishing kinetic diversity among myosins (4).

Fig. 1.

(A, Inset) The structure of apo-Myo1b (PDB ID code 4L79) showing the NTR (green) sandwiched between the motor domain, the LAH, and the bound calmodulin (red) (4). The myosin is colored gray and residues that create the hydrophobic pocket are colored in yellow. (A) Close-up of the hydrophobic pocket showing the NTR residues (L10, L11, and M14) that reach into the pocket. (B) Alignment of the initial sequences of Myo1b and Myo1c. The green box encloses the regions we define as the NTR. Conserved residues are highlighted in blue. (C) Sequence maps of myosin constructs.

To investigate whether the NTR of Myo1c plays a role in mechanosensing, we expressed Myo1c constructs with the native NTR present, with the NTR deleted, and with the Myo1b NTR in place of the native sequence and measured their kinetic and mechanical properties in the presence and absence of force. We find that the NTR of Myo1c plays important roles in tuning Myo1c’s kinetics in the presence and absence of load and in stabilizing the post–power-stroke conformation. Importantly, appending the Myo1b NTR to Myo1c causes the myosin to behave more like Myo1b; specifically, it causes the rate of actoMyo1c detachment to become sensitive to forces <1 pN and it changes the identity of the primary force-sensitive transition that limits actin detachment. These results clearly identify the NTR as an important structural element that helps define myosin-I’s force-sensing and power-generating properties. Moreover, these results suggest that mechnochemical tuning by the NTR is an underappreciated mechanism for generating functional diversity within the myosin family of motors.

Results

We probed the role of the NTR in tuning Myo1c mechanochemistry by examining the biochemical, mechanical, and motile properties of three truncated, recombinant Myo1c constructs (Fig. 1C): a protein with the native NTR sequence (Myo1c), a construct lacking the NTR (Myo1c^ΔN), and a Myo1c with the Myo1b NTR (Myo1c^ΔN->b). All constructs included the motor domain, the LAH consisting of the three calmodulin-bound IQ motifs, a FLAG-tag for purification, and an AviTag for site-specific biotinylation.

Biochemical Analysis of actoMyo1c Detachment Kinetics.

The actin detachment rate of cycling Myo1c is kinetically limited by the sequential steps of ADP release (k₊₅′) and ATP binding (k₊₂′; Scheme 1), where the rate of ADP release limits the Myo1c motility rate at saturating [ATP] (10). We used stopped-flow transient kinetic techniques to determine whether these steps were altered by deletion or swapping of the NTR (Table 1; see Materials and Methods for details). The rate constant for ATP-induced dissociation was measured by mixing pyrene-labeled actomyosin with varying ATP concentrations (Fig. 2). Similar to Myo1c (10), fluorescence transients obtained with Myo1c^ΔN and Myo1c^ΔN->b are best fitted by the sum of two exponential functions. The fast component has a hyperbolic dependence on the [ATP] (Fig. 2A) and was modeled as shown in Scheme 1 (20). Both Myo1c^ΔN and Myo1c^ΔN->b have substantially accelerated maximal rates of ATP binding (k₊₂′ = 160 ± 4.6 s⁻¹ and 160 ± 2.8 s⁻¹ for Myo1c^ΔN and Myo1c^ΔN->b, respectively) compared with Myo1c (k₊₂′ = 18 ± 0.99 s⁻¹; P < 0.001). The rate of the slow phase measured for both Myo1c^ΔN (k_slow = 56 ± 3.2 s⁻¹) and Myo1c^ΔN->b (k_slow = 54 ± 2.0 s⁻¹) is >10-fold faster than that found for Myo1c (k_slow = 4.0 ± 0.034 s⁻¹; P < 0.001) (Fig. 2B). In Myo1c, the slow phase is due to an isomerization of actin-bound myosin from a nucleotide-free state that is not capable of binding ATP to a state than can bind ATP (12, 21); however, it does not appear that the slow phase observed for the NTR mutants correlates with the same transition (see below).

Scheme 1.

Table 1.

Rate and equilibrium constants for key steps of the actomyo1c ATPase

Parameter	Myo1c	Myo1cΔN	Myo1cΔN->b
ATP binding
1/K1′, µM	120 ± 31†	450 ± 48	320 ± 24
k+2′, s−1	18 ± 0.99†	160 ± 4.6	160 ± 2.8
K1′k+2′, µM−1⋅s−1	0.15 ± 0.038†	0.35 ± 0.039	0.49 ± 0.038
k+α or k+slow, s−1	4.0 ± 0.034†	56 ± 3.2	54 ± 2.0
k−α or k−slow, s−1*	12 ± 1.2†	32 ± 4.7	58 ± 13
Afast:Aslow	0.33 ± 0.034†	1.8 ± 0.25	0.94 ± 0.21
ADP release
k+5′ (fast), s−1	3.9 ± 0.06†	4.2 ± 0.18 (21%)	0.68 ± 0.033
k+5′ (slow), s−1		0.93 ± 0.010 (79%)
K5′, µM	0.22 ± 0.05†	0.42 ± 0.015	0.16 ± 0.062

KMg25 buffer: 60 mM Mops (pH 7.0), 25 mM KCl, 1 mM EGTA, 1 mM DTT, 1 mM MgCl₂, 20 °C.

^*Calculated.

^†Values are from ref. 10.

Fig. 2.

Stopped-flow transient kinetic measurements. (A–C) The rate of ATP-induced actomyosin dissociation was measured by rapidly mixing pyrene-actomyosin with varying [ATP] and then observing the increase in pyrene fluorescence as myosin dissociated from the actin. Data were best fitted by the sum of two exponential functions. Each point is the average of at least five measurements. (A) The rate of the fast phase of the fluorescence transient as a function of [ATP]. A hyperbola was fitted to the data to yield the equilibrium constant for ATP binding (K₁′) and the maximal rate of ATP-induced dissociation (k₊₂′). Values for these rates can be found in Table 1. The maximal rate of ATP binding is faster in the deletion and swap constructs. (B) The rate of the slow phase of the fluorescence transient as a function of [ATP]. A hyperbola was fitted to the data to yield k_+α or k_+slow. (C) The ratio of the fast (A_fast) to slow (A_slow) amplitudes of the fluorescence transients as a function of [ATP]. (D) Fluorescence transients showing rate of ADP release from actomyosin. A total of 10 µM Mg.ADP equilibrated with 0.5 µM pyrene-actomyosin was rapidly mixed with 5 mM Mg.ATP (all concentrations after mixing) and the increase in fluorescence was measured as actomyosin dissociated. Note that apparent changes in the variance are due to changes in the sampling rate during acquisition to look for fast phases in the transient. (E) The affinity of actomyosin for ADP. Actomyosin was preincubated with ADP and the fractional amplitude of the slow phase of ATP-induced actomyosin dissociation was measured as a function of [ADP]. A quadratic function was fitted to the data to obtain the ADP affinity (Table 1).

The rate of ADP release was measured by preincubating pyrene-labeled actomyosin with saturating [ADP] and then observing the increase in fluorescence upon ATP-induced actomyosin dissociation (Fig. 2D). The rate of ADP release from Myo1c (k₊₅′ = 3.9 ± 0.060 s⁻¹) was reported previously (10). For Myo1c^ΔN, the fluorescence transient is best described by the sum of two exponential functions where the slower phase (0.93 ± 0.010 s⁻¹) makes up 79% of the amplitude and the faster phase (4.2 ± 0.18 s⁻¹) makes up 21% of the amplitude. For Myo1c^ΔN->b, the fluorescence transient is best fitted by a single exponential function (k₊₅′ = 0.68 ± 0.033 s⁻¹). Removal of the Myo1c NTR causes a twofold weakening in the ADP affinity (K₅ = 0.42 ± 0.015 µM; P < 0.001; Fig. 2E) compared with native Myo1c (K₅ = 0.22 ± 0.050 µM), which is reversed when the Myo1b NTR is appended (K₅ = 0.16 ± 0.062 µM; P = 0.1).

The rates of ADP release (k₊₅′) and the slow phase of ATP-induced actomyosin dissociation (k_+α; Scheme 1) are similar to each other in Myo1c (10, 12, 14) and other myosins (21, 22), leading to the suggestion that these rates are reporting a transition between similar structural states (21, 22). Interestingly, these rates are not correlated in either Myo1c^ΔN or Myo1c^ΔN->b, suggesting that the slow phase of ATP-induced dissociation and ADP release are distinct transitions in the ATPase pathway and that changes to the NTR cause uncoupling of these transitions.

Unloaded Actin Filament Gliding Assays.

In vitro motility assays in which fluorescently labeled actin filaments are propelled by surface-bound myosin molecules were conducted at 37 °C (Fig. 3A). For Myo1c, removal of the NTR causes a reduction in the sliding velocity from 83 ± 5.9 nm/s to 60 ± 4.6 nm/s (P < 0.001). Appending the Myo1b NTR causes a further reduction in sliding velocity to 32 ± 4.9 nm/s (P < 0.001). These results are consistent with the rate of ADP release limiting Myo1c sliding velocity, because the rate of ADP release for Myo1c > Myo1c^ΔN > Myo1c^ΔN->b (Fig. 2D).

Fig. 3.

(A) The rate of actin gliding by myosin was measured using the in vitro motility assay. Error bars show the SD (n = 50–75 filaments). (B) Optical trapping techniques were used to measure single-molecule interactions between actin and myosin at 50 µM ATP. Cumulative distributions of attachment durations were generated and were fitted by either single- or double-exponential functions as justified by an F-test. Distributions were normalized to account for the dead time. The rates obtained from the fitting are reported in Table 2. (C) Sample data traces showing interactions between actin and myosin in the absence of positional feedback. Individual binding interactions are denoted by black lines. Boxes show expanded interactions with blue asterisks marking force reversals. (D) Ensemble averages of the myosin working stroke were constructed by averaging individual binding interactions as previously described (5). The curvy black lines mark a break in the time of the time-reverse averages, 1 s before actomyosin detachment. Values obtained from fitting of the averages are reported in Table 2. The cartoon shows a model for a generic myosin with a two-substep power stroke. The swap and deletion constructs do not have an observable second substep in their working strokes.

Measurement of actoMyo1c Attachment Durations Using Optical Trapping Techniques.

Mechanical interactions of Myo1c^ΔN and Myo1c^ΔN->b with actin were measured using an assay in which single actin filaments were suspended between two optically trapped beads and lowered onto pedestal beads sparsely coated with myosin (23, 24). Mechanical interactions between actin and myosin were identified, cumulative distributions of attachment durations were constructed, and single- or double-exponential functions were fitted to the data as justified by statistical testing (Table 2 and Fig. 3 B and C) (Materials and Methods).

Table 2.

Mechanical and kinetic parameters determined via optical trapping techniques

Parameter	Myo1c, n = 369	Myo1cΔN, n = 550	Myo1cΔN->b, n = 230
Actomyosin detachment rate in the absence of force
kfast, s−1	3.5 ± 0.012*	2.7 ± 0.12 (37%)	9.8 ± 0.29 (28%)
kslow, s−1	NA	0.73 ± 0.026 (63%)	0.35 ± 0.049 (72%)
	Myo1c, n = 369	Myo1cΔN, n = 550	Myo1cΔN->b, n = 230
Working stroke displacements
Total, nm	7.8 ± 0.05*	5.9 ± 0.5	4.1 ± 0.3
Substep 1, nm	5.8 ± 0.03*	5.9 ± 0.5	4.1 ± 0.3
Substep 2, nm	2.0 ± 0.03*	NA	NA
	Myo1c, n = 670	Myo1cΔN, n = 153	Myo1cΔN->b, n = 316
Force sensitivity
kf, s−1	29 (+9/−6)*	NA	1.2 (+0.42/−0.27)
ddet, nm	5.2 (+0.5/−3.6)*	NA	5.3 (+1.3/−0.96)
ki, s−1	5.6 (+1.6/−0.8)*	0.51 (+0.24/−0.15)	0.059 (+0.027/−0.020)

NA, not applicable.

^*Values are from ref. 10.

The distribution of Myo1c attachment durations was previously reported to be best fitted by a single-exponential function with a rate that is consistent with the rate of ADP release measured biochemically (Fig. 3B) (10). The distribution of Myo1c^ΔN attachment durations is best fitted by the sum of two exponential functions. The rates of the fast (2.7 ± 0.12 s⁻¹) and slow (0.73 ± 0.026 s⁻¹) phases are within twofold of the rates of the fast and slow phases of ADP release measured in the stopped flow (4.2 s⁻¹ and 0.93 s⁻¹, respectively). The relative amplitudes of the fast (37%) and slow phases (63%) for actomyosin detachment are also within 20% of the relative amplitudes of the fast (21%) and slow (79%) phases of ADP release measured in the stopped flow. Myo1c^ΔN->b attachment durations are best fitted by the sum of two exponential functions, where the predominant phase (72% of the amplitude) has a rate (0.35 ± 0.049 s⁻¹) that is approximately twofold slower than expected from ADP release measurements. The slower rate may be due to the force sensitivity of actoMyo1c^ΔN->b dissociation (see below). The fast phase (9.8 ± 0.29 s⁻¹) does not correlate with any measured biochemical transition and may represent detachment of actomyosin through a noncanonical pathway.

Mechanics of the Myo1c Working Stroke.

Myo1c was shown to have a two-substep working stroke, with an initial displacement (5.8 ± 0.03 nm, state 1) that correlates with the transition to strong binding and phosphate release followed by a second displacement (2.0 ± 0.03 nm, state 2) that correlates with the rate of ADP release (Fig. 3D) (10). To examine whether deleting or changing the NTR affects the size and/or kinetics of working-stroke substeps, we ensemble averaged Myo1c^ΔN and Myo1c^ΔN->b unitary displacements acquired using the optical trap (25, 26). Averages were obtained by aligning interactions upon their initial actin attachment (time forward) and upon actin detachment (time reverse; Fig. 3D).

Myo1c^ΔN and Myo1c^ΔN->b show considerable force fluctuations during actomyosin interactions, unlike Myo1c (Fig. 3C). Strikingly, neither time-forward nor time-reversed ensemble averages of the Myo1c^ΔN and Myo1c^ΔN->b working strokes show exponential rises in force associated with mechanical substeps; rather, the force appears to fluctuate about a mean value (Fig. 3D). Therefore, a clearly resolved second mechanical substep is not observed in the ensemble averages of either Myo1c^ΔN or Myo1c^ΔN->b, likely due to the absence of a second substep, the introduction of compliance when the native Myo1c NTR is altered, and/or fluctuations between conformational states that are not tightly linked to biochemical states (27).

Force Sensitivity of Actomyosin Detachment.

To examine whether the NTR plays a role in tuning the loaded mechanochemistry of Myo1c, a feedback system was used to maintain the actin near its isometric position while myosin undergoes its working stroke (23, 28). The isometric optical clamp allows measurement of actin-attachment durations over a range of loads in each experiment. Fig. 4A shows representative data traces of actomyosin interactions collected using the isometric optical clamp. In the presence of forces that resist the power stroke, Myo1c binding interactions are generally short lived and the force remains relatively constant throughout the binding interactions. Attachment durations of actoMyo1c^ΔN interactions are slightly longer and appear to be force independent. However, in some binding interactions, the force dramatically fluctuates during the interaction in a behavior we termed force reversals. Force reversals are not due to dissociation and rebinding of actoMyo1c^ΔN, because the force covariance of the optically trapped beads remains low during the force reversals. The force reversals do not appear to represent transitions between states 1 and 2 revealed in the Myo1c ensemble averages (Fig. 3D). Rather, we propose that they represent a destabilization of the post–power-stroke state, evidenced by the fact that the force exerted by the myosin will occasionally drop to 0 pN (i.e., the baseline when actomyosin is dissociated) during a force reversal (Fig. 4A). The durations of actoMyo1c^ΔN->b attachments appear to increase with force, suggesting that the actomyosin detachment rate is more force sensitive than the other two constructs. The force-reversal behavior is also more pronounced in Myo1c^ΔN->b interactions.

Fig. 4.

Optical trapping experiments using the isometric optical clamp to apply a load to the myosin. (A) Representative data traces showing interactions between actin and myosin. Individual interactions identified by analysis of the force covariance of the optically trapped beads are marked by black bars. The binding interactions for Myo1c^ΔN->b are longer lived than the interactions for Myo1c and frequent force reversals are observed during single attachment events. (B) Mean detachment rate of actomyosin measured in the presence of force. A positive force is defined as a force that resists the power stroke. Each point is the average of 20 binned binding interactions. Different kinetic models were fitted to the unbinned data using maximum-likelihood estimation (MLE), and the best model was selected based on statistical testing as described in Materials and Methods. The thick line shows the best fit determined by MLE fitting and the thinner lines show the 95% confidence intervals. The force-sensing behaviors of the various constructs are different. The detachment rate of actoMyo1c is independent of forces <1 pN, whereas the detachment rate of actoMyo1c^ΔN->b is sensitive to these forces. The transition that limits detachment at 0 pN force (i.e., the rate of ADP release) is force insensitive for Myo1c and Myo1c^ΔN and force sensitive for Myo1c^ΔN->b.

Actomyosin attachment durations were measured as a function of the average force on the myosin during the binding interaction, and maximum-likelihood estimation (MLE) was used to fit four different kinetic models to the data (Scheme 2). The model that best fitted the data was selected based on statistical testing (Materials and Methods and Table S1). As demonstrated previously (10), the force dependence of actoMyo1c detachment is best modeled as two sequential transitions, one force independent and one force dependent (model 3; Fig. 4B and Table 2). The rate of the force-independent transition is consistent with the rate of ADP release (k₊₅′) measured via solution kinetics, whereas the rate of the force-sensitive transition is consistent with the transition that limits ATP-induced dissociation at saturating [ATP] (k₊₂′; Scheme 1) (10). In contrast, the rate of actoMyo1c^ΔN detachment as a function of force is best described by a kinetic model in which there is a single, force-independent transition that limits detachment (model 1; Fig. 4B and Table 2).

Scheme 2.

Table S1.

Values obtained from MLE fitting of the models in Scheme 2 to the data obtained with the isometric optical clamp (Fig. 4)

Parameter	ki, s−1	kf, s−1	ddet, nm	Log likelihood
Myo1c
Model 1	1.5 (+0.2/−0.2)	NA	NA	391
Model 2	NA	4.9 (+0.7/−0.7)	2.9 (+0.3/−0.3)	111
Model 3	5.6 (+1.6/−0.8)	29 (+9/−6)	5.2 (+0.5/−0.6)	98*
Model 4	0 (fixed at bounds)	4.9 (+0.8/−0.7)	2.6 (+0.3/−0.3)	111
Myo1cΔN
Model 1	0.51 (+0.2/−0.2)	NA	N/A	256*
Model 2	NA	0.56 (+1.1/−0.2)	0.18 (+1.4/−0.2)	256
Model 3	0.56 (fixed at bounds)	57 (+300/−57)	3.0 (+2.0/−3.0)	256
Model 4	0.48 (+0.2/−0.2)	0.02 (+1.6/−0.02)	29 (+9/−27)	254
Myo1cΔN->b
Model 1	0.23 (+0.05/−0.04)	NA	NA	788
Model 2	NA	1.2 (+0.4/−0.2)	3.9 (+0.6/−0.5)	623
Model 3	Fixed at bounds	1.2 (+0.5/−0.2)	3.9 (+0.9/−0.5)	623
Model 4	0.06 (+0.03/−0.02)	1.2 (+0.4/−0.3)	5.3 (+1.3/−1.0)	608*

Errors were obtained from bootstrapping simulations as described in SI Materials and Methods. The best model was selected by examining the ratio of the likelihoods as described in SI Materials and Methods. NA, not applicable.

^*The best model given the value of the log likelihood and the number of free parameters.

The distribution of actoMyo1c^ΔN->b attachment durations as a function of force is best fitted by a model in which there are two parallel pathways for detachment, one force dependent and one force independent (model 4; Scheme 2). The pathway that dominates dissociation at forces <2 pN is force sensitive, and the transition that dominates at higher loads is force insensitive. The rate of the force-sensitive transition [k_f = 1.2 (+0.42/−0.28) s⁻¹] is within twofold of the biochemical rate of ADP release with an effective distance to the transition state (d_det) of 5.3 (+1.3/−0.96) nm. The rate of the force-insensitive transition (k_i) is 0.059 (+0.027/−0.020) s⁻¹, which likely represents the dissociation of myosin.ADP from actin (5).

Traces obtained from single myosins contained interactions with and without force reversals. We analyzed the interactions without force reversals independently of interactions with force reversals to determine whether dwelling in force-reversed states is responsible for the force dependence of actin detachment (Fig. 5A). MLE fitting of model 4 in Scheme 2 to the data shows that the distance to the transition state (d_det) for interactions lacking [4.7 (+1.1/−0.98) nm] and possessing [4.5 (+2.2/−1.1) nm] force reversals is within 15% of the distance to the transition state for all of the binding interactions [5.3 (+1.3/−0.96) nm]. Therefore, the force reversals are not responsible for the observed force dependence of actomyosin detachment. Moreover, the rates of detachment through the force-independent pathway (k_i) both in the absence [0.076 (+0.072/−0.056) s⁻¹] and in the presence [0.040 (+0.028/−0.020) s⁻¹] of force reversals are within twofold of each other. The primary difference between interactions containing and lacking force reversals is the rate of detachment through the force-sensitive pathway [k_f = 2.0 (+0.82/−0.52) s⁻¹ and 0.65 (+0.46/−0.17) s⁻¹, respectively]. These data show that appending the Myo1b NTR to Myo1c introduces force sensitivity to the ADP release transition, a behavior that is observed in Myo1b (5, 6), but not in Myo1c (10).

Fig. 5.

Analysis of Myo1c^ΔN->b force reversals. (A) The rate of actoMyo1c^ΔN->b detachment as a function of force determined by MLE fitting for events both with (pink) and without (purple) force reversals. Each point is the average of 15 binned binding interactions. Interactions both with and without reversals are similarly sensitive to forces <1 pN. (B) The number of force reversals per actomyosin binding interaction (including interactions without force reversals) was measured, binned based on the force on the myosin immediately before the force reversal, and then normalized based on the mean attachment duration at that force. (C) Simple kinetic model used for calculating the theoretical detachment rate as a function of force (Materials and Methods). Actin-attached myosin transits between a high-force state and a low-force (i.e., force-reversed) state. (D) The theoretical detachment rate for actoMyo1c^ΔN->b as a function of force based on the kinetic scheme in C is shown in black. The green triangles are experimental data showing the binned average of 10 points and the green lines show the best fit determined by MLE (thick line) and the 95% confidence intervals (thin lines). It is important to note that the black line is a theoretical curve, not fitted to the data.

Myo1c^ΔN->b Force Reversals.

The number of force reversals per actomyosin binding interaction was calculated as a function of the average force during the interaction and then normalized based on the average length of a binding interaction at that force (Fig. 5B). Force does not change the time-normalized probability of undergoing a force reversal, demonstrating that the increased number of force reversals observed at larger forces is only due to the binding interactions becoming longer with force.

To better understand the relationship between the rate of actomyosin dissociation and the force reversal behavior, kinetic modeling was used (Fig. 5C; details in SI Materials and Methods). The modeling assumed that during a binding interaction, the myosin can transit between high- and low-force states (i.e., the force-reversed state) where the rates of entry (k_−r; Fig. 5B) and exit (k_+r; Fig. S1) from the low-force state are force independent. The myosin can detach from the actin via either the force-dependent (k_f(F)) or force-independent (k_i) pathways (Figs. 4B and 5A). The rates of these key transitions were fixed based on mechanical experiments. k_+r was fixed based on the cumulative distribution of time spent in the reversed state (Fig. S1; 1.3 s⁻¹). The equilibrium constant between the high- and low-force states in the absence of force was calculated by measuring the fraction of time spent in each substate (0.95) and this value permitted the calculation of rate of entry into the low-force state (k_−r = 1.2 s⁻¹). The force-dependent rate of actomyosin dissociation was fixed based on the force dependence of actomyosin detachment in the absence of force reversals (Fig. 5A; k_f = 2.0 s⁻¹ and d_det = 4.7 nm). The force-independent rate of detachment was fixed based on the rate of the force-independent pathway from the MLE fitting (k_i = 0.059 s⁻¹). Moreover, the data show that the high-force state is formed immediately after actomyosin association because there is not an ∼1-s delay before the development of force at the initiation of a binding interaction (Fig. 4A).

Fig. S1.

Cumulative distribution of the time spent in the force-reversed state (blue) for Myo1c^ΔN->b. The sum of two exponential functions was fitted to the data, where the predominant phase (67 ± 6.7% of the amplitude) has a rate of 1.3 ± 0.11 s⁻¹ and the minor phase has a rate of 0.26 ± 0.071 s⁻¹. The presence of the minor phase is likely due to the inability to distinguish single force reversals from multiple reversals. Given the minimum observable force reversal (i.e., 150 ms) and the rate of exit from the high-force state, the probability of a given force reversal event being made up of multiple force reversals is 17%.

A simple kinetic scheme can be constructed to describe both the force sensitivity of actoMyo1c^ΔN->b detachment and the force reversals (Fig. 5C). Using statistical kinetics (details in SI Materials and Methods and Fig. S2), it is possible to derive the theoretical overall actomyosin detachment rate as a function of force for this kinetic scheme (Fig. 5D). It is important to note that this curve is derived using statistical kinetic modeling based on the independently measured rate constants and not MLE fitting of the relationship between the mean attachment duration and the force. The theoretical rate of detachment (Fig. 5D) based on the kinetic scheme in Fig. 5C agrees well with the measured rate. This modeling indicates that the primary source of the force sensitivity of actomyosin detachment stems from force-induced slowing of exit from the high-force state.

Fig. S2.

Testing different kinetic models for actoMyo1c^ΔN->b dissociation under load. Green triangles show experimental data for the actoMyo1c^ΔN->b dissociation rate as a function of force. Each point is the average of 10 binding events. Statistical kinetics were used to calculate the theoretical dissociation rate as a function of force for four different models (Bottom): model 1, attachment in the high-force state (H) and force-dependent detachment [k_f(F)] from H (red; same scheme as Fig. 5C); model 2, attachment in the low-force state (L) and force-dependent detachment from H (black); model 3, attachment in H and force-dependent detachment from L (yellow); and model 4, attachment in L and force-dependent detachment from L (blue). As can be seen from the plots of the theoretical detachment rates (Top, solid lines), models 1 and 4 in which attachment and force-dependent detachment occur from the same state describe the data better. Model 4 also predicts that after attachment, the myosin would dwell in a low-force state for ∼1 s before the development of force; however, this is not seen in the raw data (Fig. 4A). Therefore, model 1 (Fig. 5C) best describes the data.

Discussion

The NTR of nucleotide-free Myo1b was found to be in a conformation well positioned to communicate the position of the LAH to the motor domain (4). This finding led us to the hypothesis that the NTR may be important for myosin mechanosensing. In the recently published crystal structure of Myo1c (8), the NTR was not resolved, possibly due to its conformational flexibility or changes in its position based on the nucleotide-binding state of the myosin; however, the hydrophobic cluster of residues important for positioning the Myo1b NTR in the nucleotide-free state (V17, V21, L22, L23, Y47, S50, F77, Y78, and P82 in the motor and F634 and F694 in the LAH) is also present in Myo1c (V13, V17, L18, L19, Y44, P47, F74, Y75, and P79 in the motor and F634 and F689 in the LAH). Despite these similarities, the residues important for anchoring the Myo1b NTR (L10, L11, and M15) in this pocket and for interacting with calmodulin (K7) are not conserved in Myo1c (Fig. 1 A and B), so we expected isoform-specific sequence differences to confer unique mechanical properties (4). Despite not knowing the conformation of the NTR in the Myo1c constructs, our results demonstrate clearly that the NTR of Myo1c serves an important role in defining the mechanochemical properties of the motor. Deletion of the Myo1c NTR or appending the Myo1b NTR to Myo1c leads to changes in the unloaded kinetics, speed of unloaded sliding, mechanics of the working stroke, and, strikingly, the ability of myosin to adjust its kinetics in response to load.

The NTR Tunes Myosin-I Mechanochemistry.

Although the actomyosin detachment rates and sliding velocities of Myo1c, Myo1c^ΔN, and Myo1c^ΔN->b appear to be limited by the rate of ADP release in the absence of force, the three different constructs examined have distinct responses to load. Myo1c’s actin-detachment rate is insensitive to forces <1.5 pN, but it shows force sensitivity at resisting loads >2 pN. Myo1c^ΔN’s actin-detachment rate is insensitive to forces <5 pN, and Myo1c^ΔN->b’s rate is sensitive to forces <2 pN (Fig. 4B).

The actin-detachment rate of Myo1c slows at forces >2 pN due to force-induced slowing of the rate of ATP-induced dissociation (10). This same transition might also be force sensitive for Myo1c^ΔN, but we are unable to resolve it because the rate of ATP-induced actomyosin detachment is substantially increased by the removal of the NTR (Fig. 2A and Table 1).

For both Myo1b (4) and Myo1c in the absence of load, removal of the NTR slows the rate of ADP release while accelerating the maximal rate of ATP-induced dissociation. This indicates that in the absence of load, removing the native NTR increases the activation energy barrier for ADP release while decreasing the barrier for ATP-induced dissociation. Appending the NTR of Myo1b to Myo1c is not able to rescue these changes. Although Myo1c^ΔN and Myo1c^ΔN->b have similar unloaded kinetics, a major difference in their energy landscapes becomes apparent when the myosins are placed under load. Specifically, whereas the distance to the transition state of ADP release for Myo1c and Myo1c^ΔN is <0.5 nm, it is 4.5 nm for Myo1c^ΔN->b. Thus, the transition state for ADP release from actoMyo1c^ΔN->b is more similar to the products than to the reactants (29), which is consistent with what we found previously for Myo1b (5–7). The NTR thus regulates both the height and position of the transition state. It is likely that the NTR serves as an allosteric regulator of the active-site conformation through its close positioning with the transducer and loop-helix-loop motif of the motor domain (4). The myosin-II N terminus is also positioned near these structural elements and its removal leads to slowing of the rate of ADP release (30), suggesting that the NTR may serve a similar role in some other myosin isoforms.

Although the ADP release transitions of both Myo1b and Myo1c^ΔN->b are force sensitive, the magnitude of their force sensitivities (as defined by the distance to the transition state, d_det) is different. The distance to the transition state for Myo1c^ΔN->b [4.5 (−1.1/+2.2) nm] is ∼2.5-fold smaller than for Myo1b [12 (−0.3/+1.6) nm] (5). This means that whereas 2 pN of force will slow the motility rate of Myo1b by 340-fold, it will slow the motility rate of Myo1c^ΔN->b by only 8.9-fold. Nevertheless, the data clearly demonstrate that the NTR affects both the regime of forces over which the myosin is sensitive and the kinetic transition that is affected by force.

The Native NTR Stabilizes the Post–power-Stroke Conformation.

The appearance of force reversals when the native NTR is removed or swapped indicates that the NTR plays a role in energetically stabilizing a post–power-stroke state by reducing the probability of entering the force-reversed state. Not all binding interactions from the same molecule contain force reversals, suggesting that additional interactions likely contribute to the stabilization of the post–power-stroke state. From our data, it is not clear whether the NTR plays a direct role in mechanically stabilizing this state or whether it plays a role as an allosteric regulator of the post–power-stroke state. One possibility is that force causes the dissociation and reassociation of the bound calmodulin in these constructs, leading to transient drops in force; however, additional structural information is required to better understand these interactions. The frequency of force reversals for Myo1c is increased in both Myo1c^ΔN and Myo1c^ΔN->b. Similar force reversals were also observed in a Myo1b construct lacking the NTR (4) and native myosin-V (31), which does not have an NTR that sits between the motor and the LAH. This behavior suggests a more general role of the NTR in stabilizing the post–power-stroke state. It is tempting to speculate that the myosin-V NTR is positioned to allow reversals of the power stroke, enabling the myosin to walk large distances past obstacles in the dense actin meshwork. Consistent with this idea, the frequency of undergoing a force reversal in myosin-V increases with load (31), enabling the myosin to dynamically regulate the probability of back stepping (31, 32). In contrast, by stabilizing the post–power-stroke conformation in myosin-I over a range of forces, the NTR may prevent transient drops in force that would cause actomyosin dissociation during force-induced long-lived interactions.

Relationship to Other Myosins.

The NTR sequence is highly divergent between different myosin-I isoforms, suggesting that it plays a role in generating functional diversity among family members. Moreover, it has been shown that the NTR of Myo1c is alternatively spliced, yielding isoforms with different subcellular localization (33–35). This alternative splicing might also play a role in establishing diversity of function among these different isoforms by mechanochemically tuning these myosins.

Most myosin isoforms (including myosin-II, -V, and -VI) have SH3-like domains at their NTRs. In myosin-V and -VI, the NTR does not interact with either the LAH or a conserved loop-helix-loop (LHL) motif in the motor domain (18, 19) whereas in myosin-II, it interacts with the LHL domain but not the LAH (17). The NTRs in these myosins likely also play roles in allosterically tuning myosin’s mechanochemistry. Consistent with this notion, deletion of the Dictyostelium myosin-II NTR leads to significant changes in the unloaded kinetics and actomyosin motility (30) and alternative splicing of the Drosophila muscle myosin-II NTR changes the myosin’s power output, sliding velocity, and ATPase rates (36, 37). Future studies are necessary to determine whether the role of the NTR in tuning mechanochemistry is a universal feature of myosins.

SI Materials and Methods

Protein Preparation.

Myo1c consisting of the motor domain, the regulatory domain (i.e., 3 IQ motifs), a C-terminal FLAG-tag for affinity purification, and an AviTag for site-specific biotinylation (construct PNT113) was expressed using the Baculovirus/Sf9 expression system as previously described (12). The Myo1c^ΔN construct (construct PLT52) was generated by removing the first 10 residues and appending a start methionine in the position equivalent to M14 of Myo1b. The Myo1c^ΔN->b construct (construct PLT54) was generated by appending residues 1–14 from Myo1b to the Myo1c^ΔN construct. Proteins were purified using a FLAG affinity column. Myosin was specifically biotinylated at the AviTag using biotin ligase and then further purified using a MonoQ column. Actin was purified from rabbit skeletal muscle (38) and both TRITC-phalloidin–decorated actin and pyrene-labeled actin were prepared as described previously (5). Calmodulin was expressed and purified as described previously (39). A construct of the alpha-actinin actin-binding domain fused to the HaloTag gene product was expressed and purified as previously described (10). HaloTagged alpha-actinin beads used for optical trapping were prepared as previously described (10). All experiments were performed in KMg25 buffer (60 mM Mops, pH 7.0, 25 mM KCl, 1 mM MgCl₂, 1 mM EGTA, and 1 mM DTT) in the presence of free calmodulin.

Stopped-Flow Transient Kinetics.

All stopped-flow kinetic experiments were conducted as previously described (20). Briefly, ATP-induced actomyosin dissociation and ADP release were measured by monitoring the change in the fluorescence of pyrene-labeled actin upon actomyosin dissociation. All experiments were conducted at 20 °C in KMg25 and the concentrations of ATP and ADP were measured spectroscopically for each experiment. All concentrations are given after mixing. The concentration of actin and myosin was fixed at 0.5 µM and the concentration of calmodulin was 10 µM. When measuring ATP-induced actomyosin dissociation, actomyosin was pretreated for 10 min with 0.02 units/mL apyrase to remove any residual ADP contamination. Data were analyzed as previously described (20) and either single- or double-exponential functions were fitted to the data, as justified by an F-test. Specifically, both single (model 1)- and double (model 2)-exponential functions were fitted to the data and the residual sum of squares (RSS) was calculated. The F-statistic is given by

$$F=\frac{\left({\text{RSS}}_1-{\text{RSS}}_2\right)/\left(p_2-p_1\right)}{{\text{RSS}}_2/\left(n-p_2\right)},$$ [S1]

where RSS₁ is the residual sum of squares for model 1, RSS₂ is the residual sum of squares for model 2, p₁ is the number of fitting parameters for model 1, p₂ is the number of fitting parameters for model 2, and n is the number of points. The F-statistic was then compared with the F-distribution with (p₂ − p₁, n − p₂) degrees of freedom to test whether the additional degrees of freedom associated with two exponential functions are warranted. Significance was set at P < 0.05. Statistical comparisons between parameters derived from fits were done using a two-tailed t test and the Holm–Bonferroni correction was applied when appropriate. Errors for calculated parameters were calculated by propagating the uncertainties.

In Vitro Actin Gliding Assays.

In vitro motility assays were conducted as previously described (12). Chambers were coated with nitrocellulose and solutions were added to the flow chamber in the following order: 0.1 mg/mL streptavidin in water (5 min); 1 mg/mL BSA in KMg25 (2 × 5 min); 2–10 nM biotinylated myosin in KMg25 + 2 μM calmodulin (5 min); wash with KMg25 buffer plus 5 mM Mg.ATP (two times); wash with KMg25 buffer (four times); 40 nM TRITC-phalloidin–labeled F-actin; and activation buffer consisting of 1% methyl cellulose in KMg25 with 1 mg/mL glucose, 1 mg/mL BSA, 5 mM Mg.ATP, 2 μM calmodulin, 192 units/mL glucose oxidase, and 48 μg/mL catalase. Flow cell chambers were imaged every 10 s for 2–5 min at 37 °C, using MetaMorph software. Filaments were tracked using the MTrackJ plugin for ImageJ (40), allowing for the calculation of the average and SDs of the sliding speeds. Statistical comparisons were done using a two-tailed t test.

Optical Trapping Sample Preparation.

Optical trapping chambers were constructed as previously described (5, 10). Coverslips were sparsely coated with 2-µm diameter silica beads in nitrocellulose to generate pedestals for the three-bead experiment. Myosin was site-specifically adhered to the flow cell surface via a biotin–streptavidin linkage. Solutions were flowed into the chamber in the following order: 0.1 mg/mL streptavidin in water (5 min); 1 mg/mL BSA in KMg25 (2 × 5 min); 2–10 nM biotinylated myosin in KMg25 + 2 μM calmodulin (5 min); wash with KMg25 buffer (two times); and 1 nM TRITC-phalloidin–labeled F-actin in KMg25 with 1 mg/mL glucose, 1 mg/mL BSA, either 50 µM or 5 mM Mg.ATP, 2 μM calmodulin, 192 units/mL glucose oxidase, and 48 μg/mL catalase. Beads (1-µM diameter) coated with the HaloTagged alpha-actinin construct were added to the flow chamber to replace approximately one-quarter of the chamber volume. Chambers were then sealed with vacuum grease and used for at most 1.5 h.

Optical Trapping Experiments.

Using a dual-beam optical trapping system and the three-bead geometry, single-molecule interactions between actomyosin were recorded as described previously (5, 23). For the experiments examining the force dependence of actomyosin detachment, an isometric optical clamp was used to apply a dynamic load to the myosin as previously described (5, 23, 28). The response time of the feedback loop was set to 50 ms. A positive force is defined as a force that resists the power stroke. In the experiments measuring the working stroke in the absence of load, experiments were conducted at 50 µM Mg.ATP. The experiments measuring the force dependence of actomyosin detachment were conducted at 5 mM Mg.ATP to ensure that the rate of ATP binding did not limit actomyosin detachment.

Optical Trapping Data Analysis.

Optical trapping interactions were identified using a covariance threshold as previously described (5). Cumulative distributions of attachment durations were generated and one or two exponential functions were fitted to the data as justified by an F-test (see above for details). Data were then normalized and scaled to account for the dead time of the instrument (∼50 ms). Ensemble averages of the working stroke were constructed by synchronizing single-molecule binding interactions forward and backward in time as previously described (5, 25). Single-exponential functions were fitted to both the time-forward and time-reverse ensemble averages.

To analyze the relationship between force and actomyosin detachment, maximum-likelihood estimation was used as previously described (5). Maximum-likelihood estimation (MLE) is necessary due to the fact that the individual binding interactions are exponentially, not normally, distributed at each force (41). For each dataset, four different kinetic models were considered (Scheme 2). The probability density function for each scheme was fitted to the data experiencing an average force of ≥ −1 pN and the likelihood was calculated. The best-fit scheme was determined using the likelihood ratio (42)

$$\text{LR}=2\ast \left(\log \left(L_2\right)-\log \left(L_1\right)\right),$$ [S2]

where L₁ and L₂ are the likelihoods of fits to the two different models. The LR value can be compared with a χ²-distribution where the number of degrees of freedom equals the difference in the number of fitted parameters between the two models. This methodology provides a statistically robust mechanism for determining whether the introduction of additional free parameters is justified by the data (42).

Force reversals were identified as previously described, using custom software written in Matlab (4). Briefly, binding interactions were selected using the covariance of the force on the two optically trapped beads. The distribution of covariances had two well-separated peaks. For an interaction to be counted as a binding event, the covariance would have to drop below a threshold set by the minimum value between the two covariance peaks. During some force reversals, the covariance would increase because the beads would both move in the same direction at the same time, making it appear that the actomyosin dissociated prematurely. As such, we used an additional threshold requiring that the covariance must transit from the peak value of the attached covariance peak to the peak value of the detached covariance peak to be counted as detachment. Using this additional criterion, it was possible to maximize the temporal resolution while preventing the appearance of premature detachments. To identify a force reversal, the force signal was filtered and marked when the signal exceeded a derivative threshold (4).

Kinetic Modeling of the Force Reversals.

It has been shown (43) that if an enzyme with N kinetic substates takes an average time, $\tau$, to complete its kinetic cycle, the total cycle time equals the product of the average lifetime of each substate times the average number of visits, n, to that substate:

$$\langle \tau \rangle =\langle n_1\rangle \ast \langle {\tau }_1\rangle +\langle n_2\rangle \ast \langle {\tau }_2\rangle +\mathrm{...}+\langle n_N\rangle \ast \langle {\tau }_N\rangle .$$ [S3]

The average lifetime of a state during a visit equals the inverse of the sum of the rates out of that state. The average number of visits to a given state is given by (43)

$$\langle n\rangle =\frac{p_{\text{o}}}{p},$$ [S4]

where p_o is the probability of visiting the state for the first time and p is the probability of leaving the state and not returning.

For the kinetic scheme describing the force reversals (Fig. 5C), the average lifetime of the low-force state during a visit is given by

$$\langle {\tau }_{\text{L}}\rangle =\frac{1}{k_{+\text{r}}+k_{\text{i}}}$$ [S5]

and the average lifetime of the high-force substate during a visit is given by

$$\langle {\tau }_{\text{H}}\rangle =\frac{1}{k_{-\text{r}}+k_{\text{f}}\left(F\right)+k_{\text{i}}}.$$ [S6]

If the myosin always starts in the high-force substate, the probability of visiting this substate the first time, p_oH = 1. The probability of leaving the high-force substate, never to return before detachment, p_H, is given by

$$p_{\text{H}}=\frac{k_{\text{f}}\left(F\right)+k_{\text{i}}}{k_{-\text{r}}+k_{\text{f}}\left(F\right)+k_{\text{i}}}+\frac{k_{-\text{r}}}{k_{-\text{r}}+k_{\text{f}}\left(F\right)+k_{\text{i}}}\ast \frac{k_{\text{i}}}{k_{+\text{r}}+k_{\text{i}}}.$$ [S7]

The probability of visiting the low-force substate once, p_oL, is given by

$$p_{\text{oL}}=\frac{k_{-\text{r}}}{k_{-\text{r}}+k_{\text{f}}\left(F\right)+k_{\text{i}}}.$$ [S8]

The probability of leaving the low-force substate, never to return during the cycle, p_L, is given by

$$p_{\text{L}}=\frac{k_{\text{i}}}{k_{+\text{r}}+k_{\text{i}}}+\frac{k_{+\text{r}}}{k_{+\text{r}}+k_{\text{i}}}\ast \frac{k_{\text{f}}\left(F\right)+k_{\text{i}}}{k_{-\text{r}}+k_{\text{f}}\left(F\right)+k_{\text{i}}}.$$ [S9]

Using these equations and the kinetic parameters described in Results, it is possible to use Eq. S4 to determine the average number of visits to each substate and then use Eq. S3 to determine the theoretical lifetime of attachment as a function of force.

Different kinetic models were considered and theoretical actomyosin detachment curves were calculated as described above (Fig. S2). Data were best described (as determined by the R² value) by models in which actomyosin association and force-dependent detachment occur from the same state. A model in which attachment and force-dependent dissociation occur from the low-force state predicts that immediately after actomyosin association, the myosin would dwell in the low-force state for ∼1 s, something which is not seen (Fig. 4A). The kinetic scheme in Fig. 5C in which attachment and force-dependent detachment occur from the high-force state best describes the data.

Materials and Methods

Myo1c constructs were expressed in Sf9 cells and purified as previously described (10). These constructs were examined using stopped-flow transient kinetic techniques, optical trapping techniques, and in vitro motility assays as previously described (10). Details of experimental conditions used for the optical trapping, in vitro motility, and transient kinetic experiments are described in SI Materials and Methods. Data were analyzed using custom software written in Matlab and Labview. Details of the data analysis and kinetic modeling are described in SI Materials and Methods.